An important prerequisite for understanding the role and response of ocean ecosystems to rising atmospheric CO₂ levels and global warming is accurate and well-characterized regional, basin and global scale measurements of oceanic Net Primary Productivity (NPP). Currently gobal estimates of NPP from satellite data used in global ocean carbon cycling and climate studies, continue to suffer from uncertainties because of their dependence on: 1) satellite derived fields of phytoplankton biomass that are constructed using algorithms incapable of providing product accuracies over regional and global scales, 2) limited estimates of phytoplankton photosynthetic quantum yields (ϕ) that are currently obtained primarily aboard research vessels, and 3) inadequate methods for scaling local in-situ ϕ measurements to regional and basin scales. Here we have utilized the Absorption based Model (AbPM), that exploits the inherent optical absorption properties of phytoplankton derived from remotely sensed reflectance data rather than phytoplankton biomass as an input, and a novel bio-optical classification scheme called Bio-Optical Measurment and Evaluation System (BIOMES) for scaling limited in-situ estimates of ϕ to obtain global maps of NPP. In-situ NPP measured at three long-term time-series stations HOT (Hawaii Ocean Time series), BATS (Bermuda Atlantic Time series Study) and CARIACO (Ocean Time-Series Program from the Cariaco basin), as well as the global collection of NPP datasets have been utilized to assess and compare the performance of AbPM derived estimates of NPP. against those obtained using more widely used biomass based models.